S&P 500

Clase series de tiempo, primavera 2024

library(tidyquant)
library(tidyverse)
library(tsibble)
library(fable)
library(feasts)

Datos

data = tq_get(c("NVDA", "MSFT"), get = "stock.prices", from = "2023-01-01", to = "2024-03-29") %>% select(symbol, date, adjusted)
data

data = tq_get(c("NVDA", "MSFT"), get = "stock.prices", from = "2023-01-01", to = "2024-03-29") %>% select(symbol, date, adjusted)

returns = data %>% group_by(symbol) %>% tq_transmute(select = adjusted,
                mutate_fun = periodReturn,
                period = "daily",
                col_rename = "return")

Registered S3 method overwritten by 'data.table':
  method           from
  print.data.table     

returns

returns = pivot_wider(returns, id_cols = date, names_from = symbol, values_from = return )
returns

returns = mutate(returns, t = row_number())
returns = as_tsibble(returns, index = t)
returns

fit_var = returns %>% model(VAR(vars(unique(data$symbol))))

Error in eval(y, envir = model$data, enclos = model$specials) : 
  object 'symbol' not found

fit_var |>
  forecast(h=20) |>
  autoplot(returns)

fore = fit_var |>
  forecast(h=20)
fore

cummulative_sum_nvda = cumsum(fore$.mean[, "NVDA"])
forecast_nvda = (1+cummulative_sum_nvda)*filter(data, symbol == "NVDA")$adjusted[311]

plot(forecast_nvda)

data = pivot_wider(data, id_cols = date, names_from = symbol, values_from = adjusted)
data

data = mutate(data, t = row_number())
data = as_tsibble(data, index = t)
data

returns = data %>% difference(MSFT)

fit_var = returns %>% model(VAR(vars(NVDA, MSFT)))

report(fit_var)

fit_var = data %>% model(VAR(vars(NVDA, MSFT), ic = "bic"))
report(fit_var)

fit_var = data %>% model(var = VAR(vars(NVDA, MSFT) ~ AR(10)))

report(fit_var)

fit_var |>
  augment() |>
  ACF(.innov) |>
  autoplot()

fit_var |>
  forecast(h=20) |>
  autoplot(data)

glance(fit_var)$sigma2